Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their...Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.展开更多
隐私集合交集(private set intersection,PSI)协议一直是解决用户隐私保护需求和合作共享需求间矛盾的有效工具.面对计算资源受限场景下的多方求交计算,本文提出了支持子集匹配且可验证的云辅助多方PSI协议(tag-based and verifiable cl...隐私集合交集(private set intersection,PSI)协议一直是解决用户隐私保护需求和合作共享需求间矛盾的有效工具.面对计算资源受限场景下的多方求交计算,本文提出了支持子集匹配且可验证的云辅助多方PSI协议(tag-based and verifiable cloud-assisted multi-party PSI,TVC-MPSI).首先,TVC-MPSI应用星型网络拓扑结构,增加对单个云服务器的安全要求,仅利用密文交集基数和交集的多项式形式确保了交集的可验证性;其次,当客户端的集合包含多个子集时,引入了Pedersen门限可验证的秘密共享技术来实现对集合子集的匹配,从而实现细粒度的交集运算;除此之外,引入基于RSA的局部可验证签名算法(local verifiable aggregate signatures,LVS),保证云服务器端和客户端身份的不可伪造性;最后,通过正确性和安全性分析,以及全面的性能对比,表明协议在保证安全性的同时拥有较好的性能.展开更多
多方隐私集合交集(multiparty private set intersection,MPSI)作为安全计算领域一种保护数据安全的计算技术,支持在不泄露任何参与方隐私的前提下,计算多个参与方数据集的交集,可通过同态加密、不经意传输等技术手段实现.但现有基于同...多方隐私集合交集(multiparty private set intersection,MPSI)作为安全计算领域一种保护数据安全的计算技术,支持在不泄露任何参与方隐私的前提下,计算多个参与方数据集的交集,可通过同态加密、不经意传输等技术手段实现.但现有基于同态加密的MPSI协议存在计算效率低、交互轮数多等问题,且通过交互无法实现交集用户保密数据的计算.为此,首先基于布隆过滤器和ElGamal算法提出了n方交集用户的秘密信誉值比较协议.进一步针对查询交集失败的问题,基于信誉值过滤器和多密钥加解密,提出用户交集基数协议并完成多方秘密信誉值评估.实验结果表明,研究提出的2种协议满足半诚实安全,可抵抗n-1个参与方的合谋且执行时间优于其他方案.展开更多
基金This study has received funding by the Science and Technology Plan Project of Keqiao District(No.2020KZ58).
文摘Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.
文摘多方隐私集合交集(multiparty private set intersection,MPSI)作为安全计算领域一种保护数据安全的计算技术,支持在不泄露任何参与方隐私的前提下,计算多个参与方数据集的交集,可通过同态加密、不经意传输等技术手段实现.但现有基于同态加密的MPSI协议存在计算效率低、交互轮数多等问题,且通过交互无法实现交集用户保密数据的计算.为此,首先基于布隆过滤器和ElGamal算法提出了n方交集用户的秘密信誉值比较协议.进一步针对查询交集失败的问题,基于信誉值过滤器和多密钥加解密,提出用户交集基数协议并完成多方秘密信誉值评估.实验结果表明,研究提出的2种协议满足半诚实安全,可抵抗n-1个参与方的合谋且执行时间优于其他方案.
